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Record W3097038642 · doi:10.3366/scot.2020.0343

Realising children's rights in an ACE-aware nation

2020· article· en· W3097038642 on OpenAlexaff
Emma Davidson, Laura H. V. Wright

Bibliographic record

VenueScottish Affairs · 2020
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsInternational Institute for Child Rights and Development
Fundersnot available
KeywordsRealisationConvention on the Rights of the ChildContext (archaeology)Political scienceHuman rightsGovernment (linguistics)Representation (politics)Public administrationEconomic growthPublic relationsPoliticsLawHistory

Abstract

fetched live from OpenAlex

An established body of multi-disciplinary evidence demonstrates that children and young people's lived experiences and spheres of influence are fundamental to their wellbeing and realisation of rights, with adversity suggested to have significant and long-term consequences. For the past two decades the Scottish Government has responded with a sustained strategic commitment to children and preventive policy measures. Only recently have Adverse Childhood Experiences (ACEs) assumed a prominent role in this context. A corresponding policy development in Scotland has been on children's rights, with significant steps taken towards implementing the United Nations Convention on the Rights of the Child (CRC). This has involved a focus on incorporation, with the tag line ‘making rights real’. By analysing key literature and policy documents, this article considers the extent and shape of the interconnections between these policy areas. Informed by Carol Bacchi's problem representation framework, we identify evidence of conceptual pairing. However, deep engagement in children's rights appears to be lacking, as is children and young people's active role in national ACE-policy review and development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.026
Scholarly communication0.0130.010
Open science0.0010.007
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.286
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2020
Admission routes1
Has abstractyes

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Same venueScottish AffairsSame topicChild Abuse and TraumaFrench-language works237,207